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Many different organizations have tracked COVID in countries around the world. They have put
the data into line graphed so we can visualize trends. One organization that has done this is
WorldMeter. From this, we are able to visually compare the countries’ COVID rates and tell if
their mandates and restrictions are working. For the most part, they all follow a similar trend- peak
in early spring, drop during the summer, and a second wave in the fall/winter months.
Methodology
The data used in this study came from the COVID Tracking Project, which is a volunteer
organization launched from The Atlantic and dedicated to collecting and publishing data tracking
COVID-19 outbreak throughout the United States. Data on COVID-19 testing and patient
outcomes from all 50 states, 5 territories, and the District of Columbia were collected on a daily
basis. Most of the data compiled were taken directly from the websites of local or state/territory
public health authorities. In a case where data were missing from these websites, the missing
information was supplemented with available numbers from official press conferences with
governors or public health authorities. The website contains data from March 14 to date. For the
purpose of this study, we limited our scope to Maryland, by examining reported data from March
14 through October 20. The dataset contained the following columns:
date, state, positive, positiveIncrease, positiveCasesViral, negative, negativeTestsViral, pending,
positiveTestsViral, totalTestsPeopleViral, totalTestsViral, totalTestEncountersViral,
negativeTestsPeopleAntibody, negativeTestsAntibody, positiveTestsPeopleAntibody,
positiveTestsAntibody, positiveTestsPeopleAntigen, positiveTestsAntigen,
totalTestsPeopleAntigen, totalTestsAntigen, hospitalizedCumulative, inIcuCumulative,
onVentilatorCumulative, hospitalizedIncrease, death, deathConfirmed, deathProbble,
deathIncrease, recovered, dataQualityGrade.
See appendix B for more description of each variable. Furthermore, for the purpose of this study,
we considered only certain variables that were found important after performing some basic data
wrangling (cleansing) as seen in the results.
We used R-Studio (Version 1.3.1073) as the integrated development environment for statistical
computation, analysis, and visualization of our data.